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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Variational quantum simulation of the critical Ising model with symmetry averaging

Here we investigate the use of deep multiscale entanglement renormalization ansatz (DMERA) circuits as a variational ansatz. We use the exactly solvable one-dimensional critical transverse-field Ising model as a test bed. Numerically exact simulation of the quantum circuit ansatz can in this case be carried out to hundreds of qubits by exploiting efficient classical algorithms for simulating matchgate circuits. We find that, for this system, the DMERA strongly outperforms a standard quantum approximate optimization algorithm (QAOA)–style ansatz, and that a major source of systematic error in correlation functions approximated using the DMERA is the breaking of the translational and Kramers-Wannier symmetries of the transverse-field Ising model. We are able to reduce this error by up to four orders of magnitude by symmetry averaging, without incurring additional cost in qubits or circuit depth. Here, we propose that this technique for mitigating systematic error could be applied to noisy intermediate-scale quantum (NISQ) simulations of physical systems with other symmetries.

1-dimensional spin chains↗
DOE OSTI2021

Application of transport-based metric for continuous interpolation between cryo-EM density maps

Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years in structural biology, to collect single images of macromolecules "frozen in time". As this technique facilitates the identification of multiple conformational states adopted by the same molecule, a direct product of it is a set of 3D volumes, also called EM maps. To gain more insights on the possible mechanisms that govern transitions between different states, and hence the mode of action of a molecule, we recently introduced a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. This tool is based on recent advances made in optimal transport, that allow efficient evaluation of Wasserstein barycenters of 3D shapes. As the overall performance of the method depends on various key parameters, including the sensitivity of the regularization parameter, we performed various numerical experiments to demonstrate how MorphOT can be applied in different contexts and settings. Finally, we discuss current limitations and further potential connections between other optimal transport theories and the conformational heterogeneity problem inherent with cryo-EM data.

3D shapes↗
DOE OSTI2020

Clumped 13 CH 2 D and 12 CHD 2 compositions of methyl groups from wood and synthetic monomers: Methods, experimental and theoretical calibrations, and initial results

Methyl groups are found in numerous biogenic and synthetic materials including geologically preserved materials such as wood. The carbon and hydrogen isotope compositions of methyl groups are used as tracers in biogeochemical cycles, as paleothermometers, and to determine the hydrogen isotopic composition of ancient rain. Here we present analyses of resolved 13 C–D ( 13 CH 2 D) and D–D ( 12 CHD 2 ) clumped isotope compositions of methyl groups as new variables for the study of methyl groups in the present and past. We first present chemical methods to extract, purify, and derivatize methyl groups from methoxyl (R–O–CH 3 ) groups as CH 3 F and CH 3 Cl, and high-resolution mass spectrometric techniques to determine the clumped isotope compositions of these species. We achieve precisions for 13 C–D clumping of ±0.25‰ and D–D clumping of ±2.5‰. We anchor our clumped isotopic measurements to a thermodynamic reference frame by first calculating the theoretical temperature dependences of 13 C–D and D–D clumping in CH 3 Cl, then placing our measurements onto this reference frame through experimental internal isotopic equilibration of CH 3 Cl at 200 °C. Finally, we provide and analyze an initial dataset of clumped 13 C–D and D–D compositions of methyl groups from various commercial/synthetic monomers and environmental woods. We observe ranges in clumped isotope compositions of ~11‰ in 13 C–D and ~48‰ in D–D, and systematic differences within these ranges between methyl groups from commercial monomers and wood. Specifically, commercial clumped 13 C–D compositions are between 0 and 3‰, which correspond to apparent equilibrium temperatures between 170 °C and the infinite temperature limit. In contrast, the clumped 13 C–D compositions of wood methoxyl groups are distinctively high (9.50–11.25‰) and 3–6‰ higher than would be expected if formed in internal isotopic equilibrium at Earth-surface temperatures. Commercial/synthetic methyl and wood methoxyl clumped D–D compositions are also distinct: -5 to +13‰ in commercial monomers vs. -35 to -8‰ in wood—such negative values cannot result from formation in isotopic equilibrium and require kinetic processes to have occurred. Overall, these results indicate that wood methoxyl groups are formed out of isotopic equilibrium and that clumped isotope compositions of methyl groups may be useful tracers of methyl group sources and sinks in the environment. For instance, isotopic clumping in methyl groups may be useful for understanding controls on isotopic clumping in methane produced by methylotrophic methanogens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Synchrotron intensity gradient revealing magnetic fields in galaxy clusters

Magnetic fields and their dynamical interplay with matter in galaxy clusters contribute to the physical properties and evolution of the intracluster medium. However, the current understanding of the origin and properties of cluster magnetic fields is still limited by observational challenges. In this article, we map the magnetic fields at hundreds-kpc scales of five clusters RXC J1314.4-2515, Abell 2345, Abell 3376, MCXC J0352.4-7401, and El Gordo using the synchrotron intensity gradient technique in conjunction with high-resolution radio observations from the Jansky Very Large Array (JVLA) and the Karoo Array Telescope (MeerKAT). We demonstrate that the magnetic field orientation of radio relics derived from synchrotron intensity gradient is in agreement with that obtained with synchrotron polarization. Most importantly, the synchrotron intensity gradient is not limited by Faraday depolarization in the cluster central regions and allows us to map magnetic fields in the radio halos of RXC J1314.4-2515 and El Gordo. We find that magnetic fields in radio halos exhibit a preferential direction along the major merger axis and show turbulent structures at higher angular resolution. The results are consistent with expectations from numerical simulations, which predict turbulent magnetic fields in cluster mergers that are stirred and amplified by matter motions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Optimization-Inspired Pin-Fin Array for Supercritical Carbon Dioxide Recuperator

Additively manufactured heat exchangers are one possible route to cost-effective sCO 2 power cycles. In this paper, experimental results are obtained for two helical pin fin tubes that were designed following parametric optimization of the fin array. Neither the numerical optimization nor the experimental testing have been previously reported in the literature. The two tube designs were, (1) the optimization inspired design, and (2) the optimization-inspired design with a fin diameter increased by a factor of 2. To characterize the print, the designs were scanned using X-ray computed tomography to measure feature sizes and heat transfer area. The optimization was conducted in a commercial, computational fluid dynamics code. The code solved the Reynolds Averaged Navier-Stokes (RANS) and energy equations with turbulence closure provided by the shear stress transport (SST) k-ω model. In the experiments, the Nusselt number augmentation was measured using the Wilson plot technique and the friction factor was determined with mass flow and pressure drop measurements. The experimental testing indicated that the optimization-inspired design had a friction factor that was four times less than the baseline tube design at equal Nusselt number. Additionally, the optimization-inspired design had a 14% improvement in Nusselt number, at equal friction factor, relative to the best performing computational fluid dynamics (CFD) trial points. Tube design (2), with the larger diameter pin fins, had similar performance, within experimental error, as the tube with the smaller diameter pin fins (1). Both tubes achieved overall fin array efficiencies near 1. A performance factor, V/V 0 , equal to the volume of the enhanced heat exchanger divided by the volume of the baseline (no-fins) heat exchanger, is recommended to quantify internal cooling performance. In conclusion, the experimental shell and tube heat exchanger, using the additively manufactured tube, is competitive with printed circuit heat exchangers in its pressure drop class and could be further improved by optimizing a shell-and-tube heat exchanger utilizing this heat transfer enhancement feature.

42 ENGINEERING↗
DOE OSTI2020

Regular sensitivity computation avoiding chaotic effects in particle-in-cell plasma methods

Particle-in-cell (PIC) simulation methods are attractive for representing species distribution functions in plasmas. However, as a model, they introduce uncertain parameters, and for quantifying their prediction uncertainty it is useful to be able to assess the sensitivity of a quantity-of-interest (QoI) to these parameters. Such sensitivity information is likewise useful for optimization. However, computing sensitivity for PIC methods is challenging due to the chaotic particle dynamics, and sensitivity techniques remain underdeveloped compared to those for Eulerian discretizations. This challenge is examined from a dual particle–continuum perspective that motivates a new sensitivity discretization. Two routes to sensitivity computation are presented and compared: a direct fully-Lagrangian particle-exact approach provides sensitivities of each particle trajectory, and a new particle-pdf discretization, which is formulated from a continuum perspective but discretized by particles to take the advantages of the same type of Lagrangian particle description leveraged by PIC methods. Since the sensitivity particles in this approach are only indirectly linked to the plasma-PIC particles, they can be positioned and weighted independently for efficiency and accuracy. The corresponding numerical algorithms are presented here in mathematical detail. The advantage of the particle-pdf approach in avoiding the spurious chaotic sensitivity of the particle-exact approach is demonstrated for Debye shielding and sheath configurations. In essence, the continuum perspective makes implicit the distinctness of the particles, which circumvents the Lyapunov instability of the N -body PIC system. The cost of the particle-pdf approach is comparable to the baseline PIC simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

An adaptable technique for comparative image assessment: Application to crosswell electromagnetic survey design for fluid monitoring

Reservoir integrity stewardship accompanying carbon capture and sequestration considers fluid extraction and reinjection as a risk-mitigating method against overpressuring that could lead to caprock damage and ensuing [Formula: see text] leakage. Crosswell electromagnetics offers a technically viable monitoring method with the spatial volume coverage necessary for reservoir-encompassing pressure management. However, a certain logistic dilemma for deep gas sequestration into saline and thus electrically conductive aquifers is that crosswell magnetic-field measurements underperform in the imaging of more resistive plume bodies, further exacerbated when vertical arrays intersect, as opposed to surround, plumes. Furthermore, comparative synthetic-data plume imaging of such scenarios rates the information content of magnetic-field versus electric-field 3D crosswell layouts for reservoir and infrastructure conditions of a representative pilot site in a coastal area in Florida. The image quality of the resulting plume replications can be ranked numerically through a newly proposed semblance qualifier, appraising the model goodness of fit to a given reference. In contrast to common least-squares measures for goodness of fit, the semblance formulation uses classifying logistic function types, thus enabling a better distinction of predefined anomaly features.

58 GEOSCIENCES↗
DOE OSTI2023

Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2019

On the Morse Index for Geodesic Lines on Smooth Surfaces Embedded in ℝ{sup 3}

The paper is devoted to the calculation of the Morse index on geodesic lines upon smooth surfaces embedded into the 3D Euclidean space. The interest in this theme is created by the fact that the wave field composed of the surface waves slides along the boundaries guided by the geodesic lines, which, generally speaking, give birth to numerous caustics. The same circumstance takes place in problems of the short-wave diffraction by 3D bodies in the shadowed part of the surface of the body, where the creeping waves arise. Two types of geodesic flows are considered upon the surface when they are generated by a point source and by an initial wave front, for instance, by the light-shadow boundary in the short-wave diffraction by a smooth convex body. The position of the points where geodesic lines meet caustics, i.e., focal points, is found and it is proved that all focal points are simple (not multiple) irrespective of the geometric structure of the caustics arisen. The mathematical techniques in use are based on the complexification of the geometrical spreading problem for a geodesics/rays tube.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Modeling the influence of the solid electrolyte interphase on the sand’s time and dendrite formation on lithium metal electrodes

Lithium metal is a sought after battery material for its high energy density due to the low electrochemical potential and density. However, lithium metal is also highly reactive, which results in a strong propensity for dendrite formation. The Sand’s time has previously been used to predict the time of dendrite initiation on metals that do not form a solid-electrolyte interphase (SEI), but it has been shown that the Sand’s time is not accurate for lithium electrodes when using transport parameters associated with the electrolyte. Thus, we built a numerical model to simulate lithium ion transport through a growing SEI to predict the Sand’s time. The numerical model is shown to be more accurate than previous analytical solutions, especially for low current densities. We then analyze the sensitivity of the Sand’s time to different SEI properties and the chemical potential gradients present in the SEI, driving lithium transport. The results showed that high lithium concentration has a greater impact at high current density, while fast diffusivity is more important at low current density. Lastly, we modeled the influence of surface roughness on the plating evolution and chemical potential gradients when an SEI is present in comparison to the electrolyte. As a result, we demonstrate that the SEI plays a critical role in lithium electrode stability, and that improved characterization techniques are needed to better understand transport through the SEI and increase lithium metal utilization in energy storage devices.

Chemistry↗
DOE OSTI2020

SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction

Several reduced order models have been successfully developed for nonlinear dynamical systems. To achieve a considerable speed-up, a hyper-reduction step is needed to reduce the computational complexity due to nonlinear terms. Many hyper-reduction techniques require the construction of nonlinear term basis, which introduces a computationally expensive offline phase. A novel way of constructing nonlinear term basis within the hyper-reduction process is introduced. In contrast to the traditional hyper-reduction techniques where the collection of nonlinear term snapshots is required, the SNS method avoids collecting the nonlinear term snapshots. Instead, it uses the solution snapshots that are used for building a solution basis, which enables avoiding an extra data compression of nonlinear term snapshots. As a result, the SNS method provides a more efficient offline strategy than the traditional model order reduction techniques, such as the DEIM, GNAT, and ST-GNAT methods. The SNS method is theoretically justified by the conforming subspace condition and the subspace inclusion relation. It is useful for model order reduction of large-scale nonlinear dynamical problems to reduce the offline cost. It is especially useful for ST-GNAT that has shown promising results, such as a good accuracy with a considerable online speed-up for hyperbolic problems in a recent paper by Choi and Carlberg [SIAM J. Sci. Comput., 41 (2019), pp. A26--A58], because ST-GNAT involves an expensive offline cost related to collecting nonlinear term snapshots. Error analysis for the SNS method is presented. Numerical results support that the accuracy of the solution from the SNS method is comparable to the traditional methods and a considerable speed-up (i.e., a factor of two to a hundred) is achieved in the offline phase.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

History of the Chemical Stockpile Emergency Preparedness Program – Volume 2: Lessons Learned (Final Report 2026)

The CSEP Program involved multiple federal agencies, multiple states, and numerous local units of government. The involvement of diverse agencies at different levels of government led to conflict and difficulty in resolving issues. That, in turn, led to slow progress in achieving program goals. Program management was criticized repeatedly by the U.S. General Accounting Office (GAO). After other mechanisms for interagency coordination had failed to give the desired results, FEMA and the Army agreed to form site-specific and national-level IPTs. The IPTs worked well to break the logjam and accelerate implementation of the program. Key elements of the IPTs’ success included constant interagency communication, solving problems at the lowest level, and obtaining buy-in from higher authority. The IPT technique could be applied to other emergency management and homeland security programs that require interagency coordination.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Learning viscoelasticity models from indirect data using deep neural networks

In this study, we propose a novel approach to model viscoelasticity materials, where rate-dependent and non-linear constitutive relationships are approximated with deep neural networks. We assume that inputs and outputs of the neural networks are not directly observable, and therefore common training techniques with input–output pairs for the neural networks are inapplicable. To that end, we develop a novel computational approach to both calibrate parametric and learn neural-network-based constitutive relations of viscoelasticity materials from indirect displacement data in the context of multiple-physics systems. We show that limited displacement data holds sufficient information to quantify the viscoelasticity behavior. We formulate the inverse computation – modeling viscoelasticity properties from observed displacement data – as a PDE-constrained optimization problem and minimize the error functional using a gradient-based optimization method. The gradients are computed by a combination of automatic differentiation and implicit function differentiation rules. The effectiveness of our method is demonstrated through numerous benchmark problems in geomechanics and porous media transport.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Trapping light in air with membrane metasurfaces for vibrational strong coupling

Optical metasurfaces can manipulate electromagnetic waves in unprecedented ways at ultra-thin engineered interfaces. Specifically, in the mid-infrared (mid-IR) region, metasurfaces have enabled numerous biochemical sensing, spectroscopy, and vibrational strong coupling (VSC) applications via enhanced light-matter interactions in resonant cavities. However, mid-IR metasurfaces are usually fabricated on solid supporting substrates, which degrade resonance quality factors (Q) and hinder efficient sample access to the near-field electromagnetic hotspots. Besides, typical IR-transparent substrate materials with low refractive indices, such as CaF 2 , NaCl, KBr, and ZnSe, are usually either water-soluble, expensive, or not compatible with low-cost mass manufacturing processes. Here, we present novel free-standing Si-membrane mid-IR metasurfaces with strong light-trapping capabilities in accessible air voids. We employ the Brillouin zone folding technique to excite tunable, high-Q quasi-bound states in the continuum (qBIC) resonances with our highest measured Q-factor of 722. Leveraging the strong field localizations in accessible air cavities, we demonstrate VSC with multiple quantities of PMMA molecules and the qBIC modes at various detuning frequencies. Our new approach of fabricating mid-IR metasurfaces into semiconductor membranes enables scalable manufacturing of mid-IR photonic devices and provides exciting opportunities for quantum-coherent light-matter interactions, biochemical sensing, and polaritonic chemistry. The authors introduce a mid-IR metasurface fabricated by decorating a free-standing Si-membrane with air holes. The enhanced light-matter interactions in such air cavities enable vibrational strong coupling and advanced biochemical sensing.

infrared spectroscopy↗
DOE OSTI2020

Large-volume centimeter-wave cavities for axion searches

The scan rate of an axion haloscope is proportional to the square of the cavity volume. In this paper, a new class of thin-shell cavities are proposed to search for axionic dark matter. These cavities feature active volume much larger (>20×) than that of a conventional cylindrical haloscope, comparable quality factor Q, and a similar frequency tuning range. Furthermore, full 3D numerical finite-element analyses have been used to show that the TM 010 eigenmodes are singly polarized throughout the volume of the cavity and can facilitate axion-photon conversion in uniform magnetic field produced by a superconducting solenoid. To mitigate spurious mode crowding and volume losses due to localization, a pre-amplification binary summing network will be used for coupling. Because of the favorable frequency-scaling, the new cavities are most suitable for centimeter-wavelength (~ 10–100 GHz), corresponding to the promising post-inflation axion production window. In this frequency range, the tight machining tolerances required for high-Q thin-shell cavities are achievable with standard machining techniques for near-infrared mirrors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Micro-scale Numerical Investigation of Internal and Interfacial Void Defects in Adhesive on Failure Behavior of Adhesively-Bonded Materials with Rough Surfaces

This paper studied the effects of air void defects on the failure behavior of adhesively-bonded materials under global shear via micro-scale computational modeling. The numerical results indicated that interfacial void defects can largely facilitate interfacial debonding of a weaker adherend/adhesive interface under shear. However, this is not the case for a stronger adherend/adhesive interface, showing the reduction on the nominal shear strength of an adhesive joint is mainly due to internal void defects. The reduced bonding performance due to voids can be improved by leveraging an appropriate surface roughness. This preliminary investigation is a first step to better understand the micro-mechanics of interfacial failure in the adhesion of a roughened/patterned adherend via surface modification(s) and an adhesive, and also shows the importance of minimizing interfacial void defects in particular at a weaker adherend/adhesive interface via different techniques.

Qiao, Yao↗
DOE OSTI2023

Bi-fidelity modeling of uncertain and partially unknown systems using DeepONets

Recent advances in modeling large-scale, complex physical systems have shifted research focuses towards data-driven techniques. However, generating datasets by simulating complex systems can require significant computational resources. Similarly, acquiring experimental datasets can prove difficult. For these systems, often computationally inexpensive, but in general inaccurate models, known as the low-fidelity models, are available. Here in this paper, we propose a bi-fidelity modeling approach for complex physical systems, where we model the discrepancy between the true system's response and a low-fidelity response in the presence of a small training dataset from the true system's response using a deep operator network, a neural network architecture suitable for approximating nonlinear operators. We apply the approach to systems that have parametric uncertainty and are partially unknown. Three numerical examples are used to show the efficacy of the proposed approach to model uncertain and partially unknown physical systems.

MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗